Now days many users and administrators access computer network based applications such as on-line shopping, airline reservations, rental car reservations, hotel reservations, on-line auctions, on-line banking, stock market trading via the communication network. Network bandwidth management thus plays a crucial role in ensuring hassle free data transfer for such applications and users. Accordingly, it is important for a service provider (sometimes referred to as “content provider”) to provide high-quality uninterrupted services. In order to do so, it has become desirable for such service providers to perform appropriate network bandwidth capacity planning to ensure that they can adequately service the demands placed on their systems by their clients in a desired manner. Thus there arises a need for solutions that ensure that the capacity planning of the network bandwidth is done based upon several factors including workload, priority etc.
Network capacity planning is always a challenge for any enterprise due to changing workloads and applications. For example, in a banking system we can have 30% deposit transactions, 40% withdrawal transactions, and 30% inquiry transactions. First, we need to identify which transaction has more weightage or priority and accordingly one has to plan the capacity of the networks as per changing workloads, applications or transactions. The conventional way of network bandwidth sizing is to look at the overall payload requirement per type of transaction and then budget the bandwidth to manage the transaction throughput. For example, if you have an average of 2 KB data per transaction, and 100 transactions per second, then you need to size for 200 KB/sec or 1.6 Mbps of network bandwidth, outside of network overheads. We refer to this method of sizing as ‘Sizing for Throughput’.
This method of network bandwidth sizing usually works for data centers that support thousands of concurrent users. However, one also has to plan bandwidth for the user side of the network. In particular, in scenarios such as banking, financial services, and insurance the organization has a number of branches all over the country or all over the world. The number of users per branch may be of the order of 10 to 50. In such cases the conventional method of sizing for throughput may not work for network bandwidth sizing.
Consider for example the same payload of 2 KB per transaction and a branch with 10 users, on the average submitting a banking transaction once every 50 seconds. Thus we have 10 transactions per 50 seconds, leading to 0.2 transactions/sec. Going by sizing for throughput we need 0.2×2 KB=0.4 KB/sec=3.2 Kbps of network bandwidth at the branch. However, if the service level agreement is an average of 1 second in the network, then even for a single request we need 2 KB/sec=16 Kbps of network bandwidth. In other words, the methodology of sizing for throughput breaks down when we wish to size for response times as well.
Some of the inventions known to us which deals in network bandwidth capacity planning are as follows:
U.S. Pat. No. 6,765,873 filed by Fichou et al describes about a connection bandwidth management process and system for use in a high speed packet switching network. One of the main object of the invention is to provide a connection bandwidth management process and system which rely on an efficient monitoring of the network resources occupancy to re-compute the bandwidth allocated to connections boarded on a given link so that the overall bandwidth capacity of the link is not exceeded, while solving the shortcomings of the conventional oversubscription technique. This patent also describes the network bandwidth allocation based on throughput requirements or traffic requirements. However, the invention fails to present a system/process which considers network bandwidth planning by considering both throughput requirements as well as response time requirements.
U.S. Pat. No. 7,072,295 filed by Benson et al describes about the allocation of bandwidth to data flows passing through a network device. The network bandwidth is allocated to committed data traffic based on a guaranteed data transfer rate and a queue size of the network device and bandwidth is allocated to uncommitted data traffic using a weighted maximum/minimum process. The weighted maximum/minimum process allocates bandwidth to the uncommitted data traffic in proportion to a weight associated with the uncommitted data traffic. However, the invention fails to disclose process/method which performs bandwidth planning rather it proposes a method of bandwidth allocation for the network.
U.S. Pat. No. 7,336,967 filed by Kelly et al describes about a method and system for providing load-sensitive bandwidth allocation. The system, according to one embodiment of the present invention, supports a bandwidth allocation scheme in which the network elements are dynamically assigned bandwidth over the WAN based upon the amount of traffic that the respect network elements have to transmit. The specific bandwidth allocation scheme is designed to ensure maximum bandwidth efficiency (i.e., minimal waste due to unused allocated bandwidth), and minimum delay of return channel data, as described with respect to figures. The scheme is be tunable, according to the mixture, frequency, and size of user traffic. The system ensures that throughput and bandwidth efficiency is preserved during all periods of operations. However, the invention fails to present a system/process which performs planning for network bandwidth by considering both throughput requirements as well as response time requirements.
United States Publication Number 20080221941 filed by Cherkasova et al describes about a system and Method for Capacity Planning for Computing Systems. The capacity planning framework further includes a capacity analyzer that receives the determined workload profile, and determines a maximum capacity of the computing system under analysis for serving the workload profile while satisfying a defined quality of service (QoS) target. However, in this document, it assumes that sufficient network bandwidth is present for allocation to the network. Also, this patent document does not disclose the sizing for network bandwidth.
Suri et al in “Approximate Mean Value Analysis for Closed Queuing Networks with Multiple-Server Stations, Proceedings of the 2007 Industrial Engineering Research Conference” describe about the use of Closed Queuing Networks in modeling various systems such as FMS, CONWIP Material Control, Computer/Communication Systems, and Health Care. Sufi et al (2007) explains how to have efficient and accurate approximate MVA computations for multi server stations. However, in the proposed invention, the inventors have modeled network link as a single server station and can accurately use inverse of MVA to arrive at bandwidth given response time requirements.
All the above mentioned prior-arts fail to recognize the significance of bandwidth planning rather they focus on bandwidth allocation at the branch level for enterprises which have heavy workloads and applications. Also, all existing techniques, methods and processes don't consider the response time constraints.
Thus there exists a need to have a system and method for addressing the network bandwidth sizing at the branch level rather than server level and also should consider both sizing for throughput and sizing for response times for accurate planning of bandwidth allocation of networking for large enterprises which have heavy workloads and applications.